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Medical Representatives’ User Acceptance of Remote e-Detailing Technology: A Moderated Mediation Analysis of Technology Acceptance Model
OBJECTIVES: E-detailing methods have steadily evolved toward more contactless and interactive channels, which have received considerable attention during the coronavirus disease 2019 (COVID-19) crisis. Based on the technology acceptance model, this study attempted to identify medical representatives...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society of Medical Informatics
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8850167/ https://www.ncbi.nlm.nih.gov/pubmed/35172092 http://dx.doi.org/10.4258/hir.2022.28.1.68 |
Sumario: | OBJECTIVES: E-detailing methods have steadily evolved toward more contactless and interactive channels, which have received considerable attention during the coronavirus disease 2019 (COVID-19) crisis. Based on the technology acceptance model, this study attempted to identify medical representatives’ perceptions and attitudes towards individual innovativeness that affected users’ intentions to adopt new e-detailing devices utilizing information and communication technology. METHODS: The subjects of the current study were medical representatives at three major multinational or domestic pharmaceutical companies that operate in South Korea. In total, 300 questionnaires were distributed and 221 were returned. The survey elicited information on respondents’ perceived ease of use (PEOU), perceived usefulness (PU), personal innovativeness (PI), and user acceptance (UA) of remote e-detailing technology, in addition to demographic information and occupational characteristics. Structural equation models were fitted to the data. Separate analyses were conducted for different platform types, PCs and mobile devices. RESULTS: PEOU showed a statistically significant positive association with PU. PEOU, PU, and PI were associated with UA, and PI was a statistically significant moderator. On average, PEOU explained up to approximately 45% of the total variation in UA of remote e-detailing. CONCLUSIONS: The analysis supports the framework of the technology acceptance model. PEOU was a substantially strong direct predictor of UA, and PI had a statistically significant, positive moderating effect between PU and UA. Medical representatives with pro-innovative attitudes are more likely to play the role of early adopters of remote e-detailing if they find this technology to be more useful. |
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